Apps & Agents
Building with models — multi-model routing, RAG pipelines, and agent execution infrastructure.
Multi-Model Systems
Model Routingcoming soon
Classifying input difficulty and dispatching to small/medium/large models.
Cascadingcoming soon
Try a cheap model first, escalate if confidence is low — cost-quality tradeoffs.
Multi-Model GPU Sharingcoming soon
Co-locating models on shared GPUs, scheduling, memory partitioning.
Cost-Quality Optimizationcoming soon
Pareto curves, finding the optimal model mix for a given budget and quality target.
RAG Infrastructure
Embedding Pipelinecoming soon
Chunking strategies, embedding model selection, incremental index updates.
Vector Database Infrastructurecoming soon
Milvus, Faiss, Weaviate, Pinecone — index types, sharding, replication, query latency at scale.
Reranker Servingcoming soon
Cross-encoder models as second-stage filter — when and how to deploy.
End-to-End RAG Servingcoming soon
Orchestrating retriever → reranker → generator with latency budgets and caching.
Agent Infrastructure
Sandbox Typescoming soon
Containers, microVMs (Firecracker), gVisor — isolation vs startup latency tradeoffs.
Agent State Managementcoming soon
Preserving filesystem, running processes, and conversation history across tool calls.
Agent Securitycoming soon
Prompt injection into tools, filesystem escape, resource exhaustion, AppArmor/seccomp, network egress.
Agent Scalingcoming soon
Thousands of concurrent sandboxes, CPU overcommit, sandbox pooling and warm-start.
Agent Orchestrationcoming soon
Loop placement (CPU vs GPU), preemption/recovery, command log replay for state reconstruction.